RESEARCH PROJECTS

The Newman Lab investigates the mechanics and neural control of intermittent mechanical contact, an activity inherent to legged locomotion and tool manipulation in both humans and robots.

 

Research Aim 1: Understanding human interaction with objects that have complex dynamics

Wire-harness installation is currently a complex manual manipulation task in the manufacturing process of large electrical systems. Simply put, wire
Humans are capable of skillfully manipulating complex objects with their own internal dynamics, such as moving a sloshing cup of
Our research goal is to explicate the whipping action in the words of dynamic primitives – submovement, oscillation and impedance. The reason
While robot performance has seen huge improvements over the past several decades, humans still vastly outperform them at tasks that
Motor neuroscience research is primarily composed of studies investigating unconstrained motion.  Yet, interaction with constraints are essential aspects of everyday

Research Aim 2: Understanding the fundamentals of human locomotion

Humans exhibit remarkable locomotion capabilities that out-perform modern robots, while considering the complexity of the musculo-skeletal system and its ‘slow’
  In human locomotion, we continuously modulate joint mechanical impedance of the lower limb (hip, knee, and ankle) either voluntarily
While rehabilitation of upper-limb motor function with human-interactive robots has been met with success, robot-aided locomotor rehabilitation has proven challenging. Conventional therapeutic
Many lower extremity exoskeletons assist in locomotion, but for this to be possible, the exoskeleton must work in synchrony with
Balance is an unstable task that requires control of translational and rotational motions. Humans use foot-ground interaction force, characterized by

Research Aim 3: Advancing human rehabilitation with robotic therapy

This project strives to develop an inertia compensator for the InMotion2 planar robot for use in studies with human interaction.
For robotic systems to interact with or learn from the actions of surrounding humans, it is important that they can